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About:
OxCOVID19 Database: a multimodal data repository for better understanding the global impact of COVID-19
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An Entity of Type :
schema:ScholarlyArticle
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wasabi.inria.fr
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Type:
Academic Article
research paper
schema:ScholarlyArticle
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type
Academic Article
research paper
schema:ScholarlyArticle
isDefinedBy
Covid-on-the-Web dataset
has title
OxCOVID19 Database: a multimodal data repository for better understanding the global impact of COVID-19
Creator
Zarebski, Alexander
Wu, Yue
Harvey, John
Błaszczyk, Piotr
Chan, Tak-Shing
Dłotko, Paweł
Farhat, Ahmad
Gurnari, Davide
Hellmer, Niklas
Hogan, Bernie
Mahdi, Adam
Salvi, Dario
Tarassenko, Lionel
Source
MedRxiv
abstract
Oxford COVID-19 Database (OxCOVID19 Database) is a comprehensive source of information related to the COVID-19 pandemic. This relational database contains time-series data on epidemiology, government responses, mobility, weather and more across time and space for all countries at the national level, and for more than 50 countries at the regional level. It is curated from a variety of (wherever available) official sources. Its purpose is to facilitate the analysis of the spread of SARS-CoV-2 virus and to assess the effects of non-pharmaceutical interventions to reduce the impact of the pandemic. Our database is a freely available, daily updated tool that provides unified and granular information across geographical regions.
has issue date
2020-08-21
(
xsd:dateTime
)
bibo:doi
10.1101/2020.08.18.20177147
has license
medrxiv
sha1sum (hex)
3c9533b3127ce6eba1e7306f28dd175d4d0f9cf7
schema:url
https://doi.org/10.1101/2020.08.18.20177147
resource representing a document's title
OxCOVID19 Database: a multimodal data repository for better understanding the global impact of COVID-19
resource representing a document's body
covid:3c9533b3127ce6eba1e7306f28dd175d4d0f9cf7#body_text
is
schema:about
of
named entity 'DATABASE'
named entity 'Oxford'
named entity 'COVID-19'
named entity 'global impact'
named entity 'China'
named entity 'database'
named entity 'United Kingdom'
named entity 'medRxiv'
named entity 'Belgium'
named entity 'CRAN'
named entity 'database'
named entity 'worldbank'
named entity 'Germany'
named entity 'Italy'
named entity 'scientific reports'
named entity 'GADM'
named entity 'medRxiv'
named entity 'CC-BY-ND'
named entity 'Brazil'
named entity 'ISO 3166-1 alpha-2'
named entity 'time series'
named entity 'epidemiological data'
named entity 'World Bank'
named entity 'COVID-19'
named entity 'EPIDEMIOLOGY'
named entity 'GIDs'
named entity 'CSV'
named entity 'GIDs'
named entity 'Cundinamarca'
named entity 'Poland'
named entity 'research groups'
named entity 'GitHub'
named entity 'standard deviation'
named entity 'public transit'
named entity 'COVID-19 pandemic'
named entity 'Met Office'
named entity 'mathematical modelling'
named entity 'Scotland'
named entity 'Database'
named entity 'precipitation'
named entity 'medRxiv'
named entity 'Borda count'
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named entity 'data sources'
named entity 'standard deviations'
named entity 'Python'
named entity 'COVID-19'
named entity 'Bogotá'
named entity 'GitHub'
named entity 'epidemiological data'
named entity 'Indonesia'
named entity 'European Values Study'
named entity 'Blavatnik School of Government'
named entity 'Ireland'
named entity 'country subdivision'
named entity 'Apple'
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named entity 'iPhone'
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named entity 'database'
named entity 'country subdivision'
named entity 'Department of Cundinamarca'
named entity 'centroid'
named entity 'CC-BY-ND'
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